SoroushVahidi/scidocs huggingface dataset:
Chapter 17 Wireless Sensor Network Security : A Survey
(2006)

As wireless sensor networks continue to grow, so does the need for effective security mechanisms. Because sensor networks may interact with sensitive data and/or operate in hostile unattended environments, it is imperative that these security concerns be addressed from the beginning of the system design. However, due to inherent resource and computing constraints, security in sensor networks poses different challenges than traditional network/computer security. There is currently enormous research potential in the field of wireless sensor network security. Thus, familiarity with the current research in this field will benefit researchers greatly. With this in mind, we survey the major topics in wireless sensor network security, and present the obstacles and the requirements in the sensor security, classify many of the current attacks, and finally list their corresponding defensive measures.
A Nonlinear Controller Based on a Discrete Energy Function for an AC/DC Boost PFC Converter
(2013)

AC/DC converter systems generally have two stages: an input power factor correction (PFC) boost ac/dc stage that converts input ac voltage to an intermediate dc voltage while reducing the input current harmonics injected to the grid, followed by a dc/dc converter that steps up or down the intermediate dc-bus voltage as required by the output load and provides high-frequency galvanic isolation. Since a low-frequency ripple (second harmonic of the input ac line frequency) exists in the output voltage of the PFC ac/dc boost converter due to the power ripple, the voltage loop in the conventional control system must have a very low bandwidth in order to avoid distortions in the input current waveform. This results in the conventional PFC controller having a slow dynamic response against load variations with adverse overshoots and undershoots. This paper presents a new control approach that is based on a novel discrete energy function minimization control law that allows the front-end ac/dc boost PFC converter to operate with faster dynamic response than the conventional controllers and simultaneously maintain near unity input power factor. Experimental results from a 3-kW ac/dc converter built for charging traction battery of a pure electric vehicle are presented in this paper to validate the proposed control method and its superiority over conventional controllers.
Tracking Sentiment in Mail: How Genders Differ on Emotional Axes
(2011)

With the widespread use of email, we now have access to unprecedented amounts of text that we ourselves have written. In this paper, we show how sentiment analysis can be used in tandem with effective visualizations to quantify and track emotions in many types of mail. We create a large word–emotion association lexicon by crowdsourcing, and use it to compare emotions in love letters, hate mail, and suicide notes. We show that there are marked differences across genders in how they use emotion words in work-place email. For example, women use many words from the joy–sadness axis, whereas men prefer terms from the fear–trust axis. Finally, we show visualizations that can help people track emotions in their emails.
Bidding algorithms for simultaneous auctions
(2001)

This paper introduces RoxyBot, one of the top-scoring agents in the First International Trading Agent Competition. A TAC agent simulates one vision of future travel agents: it represents a set of clients in simultaneous auctions, trading complementary (e.g., airline tickets and hotel reservations) and substitutable (e.g., symphony and theater tickets) goods. RoxyBot faced two key technical challenges in TAC: (i) allocation---assigning purchased goods to clients at the end of a game instance so as to maximize total client utility, and (ii) completion---determining the optimal quantity of each resource to buy and sell given client preferences, current holdings, and market prices. For the dimensions of TAC, an optimal solution to the allocation problem is tractable, and RoxyBot uses a search algorithm based on A* to produce optimal allocations. An optimal solution to the completion problem is also tractable, but in the interest of minimizing bidding cycle time, RoxyBot solves the completion problem using beam search, producing approximately optimal completions. RoxyBot's completer relies on an innovative data structure called a priceline.
Bandwidth Enhancement of a Single-Feed Circularly Polarized Antenna Using a Metasurface: Metamaterial-based wideband CP rectangular microstrip antenna.
(2016)

In this article, the authors use a 7 x 7 rectangular-ring unit metasurface and a single-feed, CP, rectangular, slotted patch antenna to enhance bandwidth. The antenna consists of a rectangular, slotted patch radiator, a metasurface with an array of rectangular-ring cells, and a coaxial feed. Using the metasurface results in a wide CP bandwidth sevenfold the size of a conventional antenna. The measured 3-dB-AR bandwidth of an antenna prototype printed onto an FR4 substrate is 28.3% (3.62 GHz-4.75 GHz) with 2:1-voltage standing wave ratio (VSWR) bandwidth of 36%. A 6.0-dBic, boresight gain with a variation of 1.5 dB is achieved across the frequency band of 3.35 GHz-4.75 GHz, with the maximum gain of 7.4 dBic at 4.1 GHz. We measure and compare the antenna prototype with a simulation using CST Microwave Studio. Parametric studies aid in understanding the proposed antenna's operation mechanism.
Dynamic Online Pricing with Incomplete Information
(2016)

Consider the pricing decision for a manager at large online retailer, such as Amazon.com, that sells millions of products. The pricing manager must decide on real-time prices for each of these product. Due to the large number of products, the manager must set retail prices without complete demand information. A manager can run price experiments to learn about demand and maximize long run profits. There are two aspects that make the online retail pricing different from traditional brick and mortar settings. First, due to the number of products the manager must be able to automate pricing. Second, an online retailer can make frequent price changes. Pricing differs from other areas of online marketing where experimentation is common, such as online advertising or website design, as firms do not randomize prices to different customers at the same time. In this paper we propose a dynamic price experimentation policy where the firm has incomplete demand information. For this general setting, we derive a pricing algorithm that balances earning profit immediately and learning for future profits. The proposed approach marries statistical machine learning and economic theory. In particular we combine multi-armed bandit (MAB) algorithms with partial identification of consumer demand into a unique pricing policy. Our automated policy solves this problem using a scalable distribution-free algorithm. We show that our method converges to the optimal price faster than standard machine learning MAB solutions to the problem. In a series of Monte Carlo simulations, we show that the proposed approach perform favorably compared to methods in computer science and revenue management. ∗Ross School of Business, University of Michigan. Contact: ericmsch@umich.edu †Rady School of Management, University of California, San Diego. Contact: kamisra@ucsd.edu ‡Department of Electrical Engineering and Computer Science, University of Michigan. Contact: jabernet@umich.edu
The biological principles of swarm intelligence
(2007)

The roots of swarm intelligence are deeply embedded in the biological study of self-organized behaviors in social insects. From the routing of traffic in telecommunication networks to the design of control algorithms for groups of autonomous robots, the collective behaviors of these animals have inspired many of the foundational works in this emerging research field. For the first issue of this journal dedicated to swarm intelligence, we review the main biological principles that underlie the organization of insects’ colonies. We begin with some reminders about the decentralized nature of such systems and we describe the underlying mechanisms of complex collective behaviors of social insects, from the concept of stigmergy to the theory of self-organization in biological systems. We emphasize in particular the role of interactions and the importance of bifurcations that appear in the collective output of the colony when some of the system’s parameters change. We then propose to categorize the collective behaviors displayed by insect colonies according to four functions that emerge at the level of the colony and that organize its global behavior. Finally, we address the role of modulations of individual behaviors by disturbances (either environmental or internal to the colony) in the overall flexibility of insect colonies. We conclude that future studies about self-organized biological behaviors should investigate such modulations to better understand how insect colonies adapt to uncertain worlds.
Illuminating Light: An Optical Design Tool with a Luminous-Tangible Interface
(1998)

We describe a novel system for rapid prototyping of laserbased optical and holographic layouts. Users of this optical prototyping tool – called the Illuminating Light system – move physical representations of various optical elements about a workspace, while the system tracks these components and projects back onto the workspace surface the simulated propagation of laser light through the evolving layout. This application is built atop the Luminous Room infrastructure, an aggregate of interlinked, computer-controlled projector-camera units called I/O Bulbs. Philosophically, the work embodies the emerging ideas of the Luminous Room and builds on the notions of ‘graspable media’. We briefly introduce the I/O Bulb and Luminous Room concepts and discuss their current implementations. After an overview of the optical domain that the Illuminating Light system is designed to address, we present the overall system design and implementation, including that of an intermediary toolkit called voodoo which provides a general facility for object identification and tracking.
Congruent evidence from α-tubulin and β-tubulin gene phylogenies for a zygomycete origin of microsporidia
(2003)

The origin of microsporidia and the evolutionary relationships among the major lineages of fungi have been examined by molecular phylogeny using a-tubulin and b-tubulin. Chytrids, basidiomycetes, ascomycetes, and microsporidia were all recovered with high support, and the zygomycetes were consistently paraphyletic. The microsporidia were found to branch within zygomycetes, and showed relationships with members of the Entomophthorales and Zoopagales. This provides support for the microsporidia having evolved from within the fungi, however, the tubulin genes are difficult to interpret unambiguously since fungal and microsporidian tubulins are very divergent. Rapid evolutionary rates a characteristic of practically all microsporidian genes studied, so determining their evolutionary history will never be completely free of such difficulties. While the tubulin phylogenies do not provide a decisive conclusion, they do further narrow the probable origin of microsporidia to a zygomycete-like ancestor. 2002 Elsevier Science (USA). All rights reserved.
Timing Attacks on Implementations of Diffie-Hellman, RSA, DSS, and Other Systems
(1996)

By carefully measuring the amount of time required to perform private key operations, attackers may be able to nd xed Di eHellman exponents, factor RSA keys, and break other cryptosystems. Against a vulnerable system, the attack is computationally inexpensive and often requires only known ciphertext. Actual systems are potentially at risk, including cryptographic tokens, network-based cryptosystems, and other applications where attackers can make reasonably accurate timing measurements. Techniques for preventing the attack for RSA and Di e-Hellman are presented. Some cryptosystems will need to be revised to protect against the attack, and new protocols and algorithms may need to incorporate measures to prevent timing attacks.
Generation of Test Cases from Software Requirements Using Natural Language Processing
(2013)

Software testing plays an important role in early verification of software systems and it enforces quality in the system under development. One of the challenging tasks in the software testing is generation of software test cases. There are many existing approaches to generate test cases like using uses case, activity diagrams and sequence diagrams; they have their own limitations such as inability to capture test cases for non functional requirements and etc. Thus these techniques have restricted use in acceptance testing and are not effective for verification & acceptance of large software system. If software requirements are stated using semi-formal or formal methods then it is difficult for the testers and other third party domain experts to test the system. It also requires much expertise in interpreting requirements and only limited number of persons can understand them. This paper proposes an approach to generate test case from software requirements expressed in natural language using natural language processing technique.
Cellular planning for next generation wireless mobile network using novel energy efficient CoMP
(2018)

Cellular planning also called radio network planning is a crucial stage for the deployment of a wireless network. The enormous increase in data traffic requires augmentation of coverage, capacity, throughput, quality of service and optimized cost of the network. The main goal of cellular planning is to enhance the spectral efficiency and hence the throughput of a network. A novel CoMP algorithm has been discussed with two-tier heterogeneous network. Number of clusters has been obtained using V-R (variance ratio) Criterion. The centroid of a cluster obtained using K-means algorithm provides the deployment of BS position. Application of CoMP in this network using DPS approach with sleep mode of power saving, provides higher energy efficiency, SINR and throughput as compared to nominal CoMP. CoMP basically describes a scheme in which a group of base stations (BS) dynamically co-ordinate and co-operate among themselves to convert interference into a beneficial signal. Network planning using stochastic method and Voronoi Tessellation with two-tier network has been applied to a dense region of Surat city in Gujarat state of India. The results show clear improvement in signal-to-interference plus noise ratio (SINR) by 25% and energy efficiency of the network by 28% using the proposed CoMP transmission.
CardBoardiZer: Creatively Customize, Articulate and Fold 3D Mesh Models
(2016)

Computer-aided design of flat patterns allows designers to prototype foldable 3D objects made of heterogeneous sheets of material. We found origami designs are often characterized by pre-synthesized patterns and automated algorithms. Furthermore, augmenting articulated features to a desired model requires time-consuming synthesis of interconnected joints. This paper presents CardBoardiZer, a rapid cardboard based prototyping platform that allows everyday sculptural 3D models to be easily customized, articulated and folded. We develop a building platform to allow the designer to 1) import a desired 3D shape, 2) customize articulated partitions into planar or volumetric foldable patterns, and 3) define rotational movements between partitions. The system unfolds the model into 2D crease-cut-slot patterns ready for die-cutting and folding. In this paper, we developed interactive algorithms and validated the usability of CardBoardiZer using various 3D models. Furthermore, comparisons between CardBoardiZer and methods of Autodesk® 123D Make, demonstrated significantly shorter time-to-prototype and ease of fabrication.
Deep Learning without Poor Local Minima
(2016)

In this paper, we prove a conjecture published in 1989 and also partially address an open problem announced at the Conference on Learning Theory (COLT) 2015. For an expected loss function of a deep nonlinear neural network, we prove the following statements under the independence assumption adopted from recent work: 1) the function is non-convex and non-concave, 2) every local minimum is a global minimum, 3) every critical point that is not a global minimum is a saddle point, and 4) the property of saddle points differs for shallow networks (with three layers) and deeper networks (with more than three layers). Moreover, we prove that the same four statements hold for deep linear neural networks with any depth, any widths and no unrealistic assumptions. As a result, we present an instance, for which we can answer to the following question: how difficult to directly train a deep model in theory? It is more difficult than the classical machine learning models (because of the non-convexity), but not too difficult (because of the nonexistence of poor local minima and the property of the saddle points). We note that even though we have advanced the theoretical foundations of deep learning, there is still a gap between theory and practice.
An approach for offensive text detection and prevention in Social Networks
(2015)

Social Network has become a place where people from every corner of the world has established a virtual civilization. In this virtual community, people used to share their views, express their feelings, photos, videos, blogs, etc. Social Networking Sites like Facebook, Twitters, etc. has given a platform to share innumerable contents with just a click of a button. However, there is no restriction applied by them for the uploaded content. These uploaded content may contains abusive words, explicit images which may be unsuitable for social platforms. As such there is no defined mechanism for restricting offensive contents from publishing on social sites. To solve this problem we have used our proposed approach. In our approach we are developing a social network prototype for implementing our approach for automatic filtering of offensive content in social network. Many popular social networking sites today don't have proper mechanism for restricting offensive contents. They use reporting methods in which user report if the content is abuse. This requires substantial human efforts and time. In this paper, we applied pattern matching algorithm for offensive keyword detection from social networking comments and prevent it from publishing on social platform. Apart from conventional method of reporting abusive contents by users our approach does not requires any human intervention and thus restrict offensive words by detecting and preventing it automatically.
Major League Soccer Scheduling Problem
(2016)

Major League Soccer is the highest level mens professional soccer league in United States and Canada, consisting of 20 teams, with 17 in United States and 3 in Canada. The League is divided by two Conferences: Western and Eastern with 10 teams each. The regular season of the League runs from early March to late October each year. It is important to look at MLS mainly for three reasons. Firstly, it is a fast-growing league, with only 10 teams competed in 1996 when the League started. Secondly, the popularity of the game has increased dramatically, with the average per-game attendance in MLS increased by 40% in the past decade, which exceeds that of NHL and NBA. Lastly, the big TV broadcasting contract signed with ESPN, Fox Sports, and Univision has demonstrated the huge commercial value of the League.
Information Security and Privacy: Rethinking Governance Models
(2010)

Concerns about information security and privacy continue to make headlines in the media and rate as serious issues in business and public surveys. Conventional thinking suggests that enhancements to governance models and business practices improve the performance of individual businesses. However, is this enough? Good governance is based on clear rights and responsibilities, and this panel will address the contention that such clarity is lacking in the treatment of personal information. As a result, certain types of business innovation may be constrained and good practices may remain tick box exercises, disconnected from wider business objectives. More radical thinking would go beyond incremental improvements to the status quo and recognize the profound challenges to privacy and information security created by digital technology. This panel will bring together a range of research disciplines and senior business representatives to critique current practice and develop a future research agenda.
Software Test Automation practices in agile development environment: An industry experience report
(2012)

The increased importance of Test Automation in software engineering is very evident considering the number of companies investing in automated testing tools nowadays, with the main aim of preventing defects during the development process. Test Automation is considered an essential activity for agile methodologies being the key to speed up the quality assurance process. This paper presents empirical observations and the challenges of a test team new to agile practices and Test Automation using open source testing tools integrated in software projects that use the Scrum methodology. The results obtained showed some important issues to be discussed and the Test Automation practices collected based on the experiences and lessons learned.
Radial-Flux Permanent-Magnet Hub Drives: A Comparison Based on Stator and Rotor Topologies
(2012)

In this paper, the performances of electric vehicle (EV) in-wheel (hub) nonoverlap-winding permanent-magnet motors with different stator and rotor topologies are compared. The calculation of the frequency losses in the design optimization of the hub motors is specifically considered. Also, the effect of the slot and pole number choice that determines the winding factor of the machine is investigated. It is shown that the torque-per-copper-loss performance of the machine cannot be judged solely on the winding factor of the machine. Wide open stator slot machines with rectangular preformed coils and, hence, low manufacturing costs are found to perform better than expected. The design detail and test results of a prototype 10-kW water-cooled EV hub drive are presented. The test results confirm the finite-element-calculated results, specifically in the high-speed region of the drive where the rotor topology affects the constant power speed range.
Fast and robust Earth Mover's Distances
(2009)

We present a new algorithm for a robust family of Earth Mover's Distances - EMDs with thresholded ground distances. The algorithm transforms the flow-network of the EMD so that the number of edges is reduced by an order of magnitude. As a result, we compute the EMD by an order of magnitude faster than the original algorithm, which makes it possible to compute the EMD on large histograms and databases. In addition, we show that EMDs with thresholded ground distances have many desirable properties. First, they correspond to the way humans perceive distances. Second, they are robust to outlier noise and quantization effects. Third, they are metrics. Finally, experimental results on image retrieval show that thresholding the ground distance of the EMD improves both accuracy and speed.